Shashank Agarwal

Institute of Electrical and Electronics Engineers | IEEE

Influencer marketing has rapidly emerged as a cornerstone of digital advertising strategies, enabling brands to connect authentically with target audiences through trusted voices on social media platforms. However, measuring the effectiveness of these campaigns has long been a challenge due to the complexity of digital ecosystems and the sheer volu...

In the current digital age, software programs and applications provide convenience and added value in a number of ways. Multi-armed Bandit algorithms (MAB) are a prime example of this; In capital markets, they assist in the adaptive design of trading strategies that adjust to market shifts and investor behavior. In e-commerce, MAB helps optimize pr...

Natural Language Processing (NLP) has evolved as a transformational force in the healthcare industry, which suggests innovative ways to extract, generate, and process clinical data. This review paper delves into the critical role of NLP in recasting the healthcare sector through the extraction of essential medical information from multiple sources,...

In an era marked by the swift integration of digital technologies into the healthcare landscape, this research paper elucidates the imperative of validating clinical applications of digital health solutions and underscores the criticality of adeptly managing the inherent risks associated with this transformation. The burgeoning adoption of digital...

In today's fast-paced and data-driven corporate market, the capacity to fully utilize information is critical. Business intelligence (BI) is the foundation of informed decision-making, allowing firms to turn unprocessed information into actionable insights. It is a process that starts with understanding data integration methodologies and learning e...

This research aims to investigate how artificial intelligence (AI) can be used to improve marketing and brand loyalty. Artificial intelligence (AI) is one of the most revolutionary technologies because it allows computers to independently execute mental skills often reserved for humans, such as problem solving and reasoning. In order to make judgme...

With the rapid digitization of banking services, modern financial institutions face a growing menace from cybercriminals. Traditional methods of fraud detection have proven inadequate against sophisticated cyber threats, prompting the adoption of advanced technologies such as machine learning. This research delves into various cyber threats face...

The financial services industry is undergoing a seismic shift, driven by the convergence of technological advancements, regulatory mandates, and changing consumer expectations. Central to this transformation is the emergence of Open Banking, a strategic initiative reshaping traditional banking paradigms by advocating for collaboration, interoperabi...

Synthetic data generation (SDG) is known as the method of training a model with machine learning techniques to recognize patterns in a real dataset. The trained model can then be used to produce fresh, or synthetic data. Synthetic data generation stands as a pivotal solution at the intersection of data privacy and medical research. This review pape...

Physician outreach plays a crucial role in effective healthcare delivery, but traditional methods have limitations in personalization and efficiency. This paper explores the application of machine learning (ML) in maximizing physician outreach and provides recommendations for successful implementation. ML techniques offer opportunities to enhance t...

In an increasingly data-driven world, businesses seek to enhance their strategies and performance through effective optimization methods. One such method is A/B testing, a potent tool enabling the comparison of different versions of products or services to determine superior performance. This research paper delves into the fundamentals of A/B testi...

Provider affiliations are critical in healthcare because they facilitate care coordination, resource allocation, referral management, and network optimization. Traditional methods of establishing and maintaining affiliations rely on manual procedures, human contacts, and geographical proximity, resulting in inefficiencies and limits in accurate r...

The present paper discusses how to learn from COVID-19 outbreak can help us take a proactive stance toward epidemic readiness by using state of the art developments in data science and artificial intelligence. It argues the importance of using an integrated data approach along with deployment of machine learning algorithms to facilitate the timely...